In the world of SQL database engines, seemingly small inefficiencies in processing an individual database query may rapidly become significant if the inefficiency affects thousands or tens of thousands of similar queries. As a result, diagnosing and resolving such inefficiencies can be of substantial importance. For greater clarity, while the term “query” is used throughout this document, it should be understood that this term is also intended to refer to any type of SQL statement, including statements that insert, delete or modify data. As will be understood by one skilled in the art, such statements are commonly referred to as “SQL statements” or DML (data manipulation language).
Although typically most database applications will receive at least some queries which share common attributes, for certain database applications many queries are of a standard or routine type. For example, in the banking industry, particularly with automated teller machines (ATMs) and credit card purchase processing, many routine SQL queries accessing basic account information will be substantially similar. Accordingly, the applicants have recognized a need for a system and methodology for efficiently grouping similar database queries and compiling processing statistics for each such group for diagnostic purposes. The present invention addresses such a need.